Data Analytics with Programming
This course gives an applied introduction to the most important techniques in business-related data analytics. Students are given hands-on experience with programming, working with data, using descriptive statistics to motivate models, and using models to turn data into actionable knowledge. Simulation techniques will be used to assess statistical tools.
- Introduction to R. Introductory descriptive statistics, data visualization and data re-organization. Introductory statistical inference.
- Data exploration and visualization in R.
- An introduction to data-modelling: Simple regression models and an introduction to simulation.
- Multiple linear regression: Dummy-variables, interaction terms, data-transformations and interpretation.
- Regression diagnostics and model selection.
Learning outcome knowledge
Central theory surrounding regression models will be developed. The students will learn applied data analytics and programming using the R software system.
- Written assignment: 40%
- Written exam: 60%